A modern data warehouse provides users with instant access to analyses of all data from different databases and systems. The analyses can be extended to include Big Data as well as the creation of machine learning models. An important element is easy operationalisation of these analyses.
A unified environment significantly reduces the time required for analytical projects. It allows for a comprehensive development of various analytical solutions.
All stakeholders can gain instant insight into the company’s operations, using the latest available data from the deployed systems at any time.
Another important aspect is data security. Unsurpassed security measures protect data. We offer the most advanced security and privacy protection functions, such as column- and row-level security measures and dynamic data masking.
The modern analytical environment in the cloud is addressed to different target groups.
They simplify the process of combining different types of data from multiple sources, including streaming, transactional and business data.
They access data sets in a secure way and use a reporting system to create dashboards and reports. They securely share data within and outside the organisation.
They match database solutions to growing requirements, manage data stores and repositories. They use well-known languages and tools such as T-SQL. They assign resources.
They protect the organisation’s data and improve its data management. They secure access and ensure privacy requirements are applied.
They work with huge amounts of data. They look for patterns, build and test models using advanced data analysis techniques.
They are the recipients of reports and manager dashboards. They analyse data contained in them, look for opportunities and make business decisions.
We understand our clients and know how difficult it is to make the transition to modern data analysis. The challenges we face are related to the complexity of environments, large amount of data (Big Data), diversity of data, variability of data over time, cost of environments, as well as insufficient knowledge and availability of people in the team. This is why we propose an iterative approach. We work in an agile way and adapt our services to your business needs. We conduct the implementation project according to the Microsoft Analytics on Azure methodology. What is important for us is demonstrating the benefits of the implementation from the very beginning of the project execution.
We start the cooperation with a pilot project. We prepare the client’s team for the implementation of a modern analytical platform – data warehouse – in the Microsoft Azure cloud. The most important goal of the project is to build the team’s competencies so they can understand the modern analytical environment in the Azure cloud and develop it further. The key points of the project are analytical workshop meetings whose aim is to gather infrastructure, data and architecture requirements. The next step is to develop a concept for working with data by identifying roles, processes, rules and defining the lifecycle of the environment. We then develop competency profiles and propose paths of future development. The project ends with a workshop demonstrating the functions of the technologies used in the architecture. We present the whole process in the workshop: data collection, data transformation, data model, data mining, reports, predictive analyses, cockpits, sharing of all analyses and teamwork.
When we talk to clients, the most common challenges we encounter are those that affect the entire organisation, the processes of data collection, storage and reporting:
Key characteristics of the service:
By implementing modern cloud analytics in your organisation, you choose to improve business performance and process efficiency, and build a data-driven organisational culture. You reduce the cost of storing and sharing a variety of data. Users work with greater satisfaction, and get new opportunities to present data as attractive reports and manager dashboards.
You build competitive advantage through faster access to reliable data, reduced time-to-market, better customer service, and increased income. New opportunities arising from the combination of relational and unstructured data provide the opportunity to launch new services or create new products.
These types of projects usually start with the production of a minimum product to quickly show the benefit of the implementation. The cost can be EUR 20,000–30,000 net, depending on the scope. Our experience indicates that the vendor’s investment funds are a great support in the launch of such projects, which allow you, among others, to launch cloud subscriptions and finance the implementation partner services. As a partner with the highest competencies, we support our customers in obtaining such investment funds.
